Triple

T16698985
Position Surface form Disambiguated ID Type / Status
Subject Wall Street E405791 entity
Predicate character P662 FINISHED
Object Darien Taylor E1049906 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Darien Taylor | Statement: [Wall Street, character, Darien Taylor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darien Taylor
Context triple: [Wall Street, character, Darien Taylor]
  • A. Darien Taylor chosen
    Darien Taylor is a fictional character from the film "Wall Street," portrayed as an ambitious interior designer romantically involved with stockbroker Bud Fox.
  • B. Cynthia Taylor
    Cynthia Taylor is a fictional character from the television series "Mozart in the Jungle," portrayed as a seasoned oboist navigating the personal and professional challenges of life in a New York symphony orchestra.
  • C. Cheryl Duffield
    Cheryl Duffield is known as the wife of American billionaire software entrepreneur and philanthropist David Duffield.
  • D. Sherry Jackson
    Sherry Jackson is an American actress best known for her work as a child and young adult performer in 1950s and 1960s film and television.
  • E. Darcy Scott
    Darcy Scott is a lively, music-obsessed protagonist whose passion for dancing shapes much of her personality and story.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3832f550c8190bf7514d4611dec6a completed April 18, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a51378788190b9f3bb0a344dcdd8 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:19 a.m.